---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: fluency-scorer
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fluency-scorer

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1451
- F1: 0.9457
- Accuracy: 0.9488
- Precision: 0.9456
- Recall: 0.9488

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log        | 0     | 0    | 0.7816          | 0.5684 | 0.4673   | 0.7714    | 0.4673 |
| 0.1379        | 1.0   | 168  | 0.1523          | 0.9426 | 0.9467   | 0.9432    | 0.9467 |
| 0.1464        | 2.0   | 336  | 0.1449          | 0.9458 | 0.9488   | 0.9456    | 0.9488 |
| 0.1592        | 3.0   | 504  | 0.1451          | 0.9457 | 0.9488   | 0.9456    | 0.9488 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0